Overview

Dataset statistics

Number of variables16
Number of observations26419
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 MiB
Average record size in memory178.2 B

Variable types

Numeric15
Categorical1

Alerts

driverId is highly overall correlated with raceId and 1 other fieldsHigh correlation
laps is highly overall correlated with positionOrderHigh correlation
milliseconds is highly overall correlated with points and 2 other fieldsHigh correlation
points is highly overall correlated with milliseconds and 2 other fieldsHigh correlation
position is highly overall correlated with positionTextHigh correlation
positionOrder is highly overall correlated with laps and 4 other fieldsHigh correlation
positionText is highly overall correlated with position and 1 other fieldsHigh correlation
raceId is highly overall correlated with driverId and 1 other fieldsHigh correlation
resultId is highly overall correlated with driverId and 1 other fieldsHigh correlation
statusId is highly overall correlated with milliseconds and 2 other fieldsHigh correlation
resultId is uniformly distributedUniform
resultId has unique valuesUnique
grid has 1627 (6.2%) zerosZeros
points has 18419 (69.7%) zerosZeros
laps has 2519 (9.5%) zerosZeros

Reproduction

Analysis started2024-06-25 01:10:15.531169
Analysis finished2024-06-25 01:11:30.948373
Duration1 minute and 15.42 seconds
Software versionydata-profiling v4.8.3
Download configurationconfig.json

Variables

resultId
Real number (ℝ)

HIGH CORRELATION  UNIFORM  UNIQUE 

Distinct26419
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13210.926
Minimum1
Maximum26424
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-25T01:11:31.106371image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1321.9
Q16605.5
median13210
Q319814.5
95-th percentile25103.1
Maximum26424
Range26423
Interquartile range (IQR)13209

Descriptive statistics

Standard deviation7627.9288
Coefficient of variation (CV)0.57739548
Kurtosis-1.1998307
Mean13210.926
Median Absolute Deviation (MAD)6605
Skewness0.00034662031
Sum3.4901944 × 108
Variance58185298
MonotonicityNot monotonic
2024-06-25T01:11:31.438577image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
17610 1
 
< 0.1%
17620 1
 
< 0.1%
17619 1
 
< 0.1%
17618 1
 
< 0.1%
17617 1
 
< 0.1%
17616 1
 
< 0.1%
17615 1
 
< 0.1%
17614 1
 
< 0.1%
17613 1
 
< 0.1%
Other values (26409) 26409
> 99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
26424 1
< 0.1%
26423 1
< 0.1%
26422 1
< 0.1%
26421 1
< 0.1%
26420 1
< 0.1%
26419 1
< 0.1%
26418 1
< 0.1%
26417 1
< 0.1%
26416 1
< 0.1%
26415 1
< 0.1%

raceId
Real number (ℝ)

HIGH CORRELATION 

Distinct1108
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean544.16746
Minimum1
Maximum1127
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-25T01:11:31.775820image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile63
Q1297
median525
Q3800
95-th percentile1057
Maximum1127
Range1126
Interquartile range (IQR)503

Descriptive statistics

Standard deviation308.13475
Coefficient of variation (CV)0.56624987
Kurtosis-1.0589833
Mean544.16746
Median Absolute Deviation (MAD)250
Skewness0.11543094
Sum14376360
Variance94947.025
MonotonicityNot monotonic
2024-06-25T01:11:32.067684image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
800 55
 
0.2%
809 47
 
0.2%
368 39
 
0.1%
363 39
 
0.1%
357 39
 
0.1%
359 39
 
0.1%
360 39
 
0.1%
744 39
 
0.1%
371 39
 
0.1%
370 39
 
0.1%
Other values (1098) 26005
98.4%
ValueCountFrequency (%)
1 20
0.1%
2 20
0.1%
3 20
0.1%
4 20
0.1%
5 20
0.1%
6 20
0.1%
7 20
0.1%
8 20
0.1%
9 20
0.1%
10 20
0.1%
ValueCountFrequency (%)
1127 20
0.1%
1126 20
0.1%
1125 20
0.1%
1124 20
0.1%
1123 19
0.1%
1122 20
0.1%
1121 20
0.1%
1120 20
0.1%
1119 20
0.1%
1118 20
0.1%

driverId
Real number (ℝ)

HIGH CORRELATION 

Distinct859
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean272.54158
Minimum1
Maximum860
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-25T01:11:32.365587image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q157
median167
Q3382
95-th percentile838
Maximum860
Range859
Interquartile range (IQR)325

Descriptive statistics

Standard deviation277.80833
Coefficient of variation (CV)1.0193246
Kurtosis-0.26771172
Mean272.54158
Median Absolute Deviation (MAD)137
Skewness1.0619364
Sum7200276
Variance77177.466
MonotonicityNot monotonic
2024-06-25T01:11:32.655792image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 387
 
1.5%
8 352
 
1.3%
1 339
 
1.3%
22 326
 
1.2%
18 309
 
1.2%
30 308
 
1.2%
20 300
 
1.1%
13 271
 
1.0%
815 266
 
1.0%
119 257
 
1.0%
Other values (849) 23304
88.2%
ValueCountFrequency (%)
1 339
1.3%
2 184
0.7%
3 206
0.8%
4 387
1.5%
5 112
 
0.4%
6 36
 
0.1%
7 27
 
0.1%
8 352
1.3%
9 99
 
0.4%
10 95
 
0.4%
ValueCountFrequency (%)
860 1
 
< 0.1%
859 5
 
< 0.1%
858 28
 
0.1%
857 29
 
0.1%
856 11
 
< 0.1%
855 51
0.2%
854 44
0.2%
853 22
 
0.1%
852 73
0.3%
851 1
 
< 0.1%

constructorId
Real number (ℝ)

Distinct211
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.641054
Minimum1
Maximum215
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-25T01:11:32.936672image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q16
median25
Q360
95-th percentile204
Maximum215
Range214
Interquartile range (IQR)54

Descriptive statistics

Standard deviation60.89551
Coefficient of variation (CV)1.2267167
Kurtosis0.99669199
Mean49.641054
Median Absolute Deviation (MAD)20
Skewness1.4989382
Sum1311467
Variance3708.2631
MonotonicityNot monotonic
2024-06-25T01:11:33.232940image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 2405
 
9.1%
1 1889
 
7.2%
3 1642
 
6.2%
25 881
 
3.3%
32 871
 
3.3%
15 803
 
3.0%
4 787
 
3.0%
9 754
 
2.9%
18 672
 
2.5%
34 662
 
2.5%
Other values (201) 15053
57.0%
ValueCountFrequency (%)
1 1889
7.2%
2 140
 
0.5%
3 1642
6.2%
4 787
 
3.0%
5 536
 
2.0%
6 2405
9.1%
7 280
 
1.1%
8 78
 
0.3%
9 754
 
2.9%
10 424
 
1.6%
ValueCountFrequency (%)
215 14
 
0.1%
214 146
0.6%
213 166
0.6%
211 76
 
0.3%
210 346
1.3%
209 78
 
0.3%
208 154
0.6%
207 112
 
0.4%
206 109
 
0.4%
205 76
 
0.3%

number
Real number (ℝ)

Distinct129
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.009501
Minimum0
Maximum208
Zeros34
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-25T01:11:33.549473image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q17
median16
Q324
95-th percentile44
Maximum208
Range208
Interquartile range (IQR)17

Descriptive statistics

Standard deviation15.405455
Coefficient of variation (CV)0.85540714
Kurtosis9.0316594
Mean18.009501
Median Absolute Deviation (MAD)8
Skewness2.3736324
Sum475793
Variance237.32806
MonotonicityNot monotonic
2024-06-25T01:11:33.838572image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 1008
 
3.8%
6 994
 
3.8%
8 993
 
3.8%
16 988
 
3.7%
11 984
 
3.7%
3 983
 
3.7%
14 965
 
3.7%
10 959
 
3.6%
20 957
 
3.6%
5 956
 
3.6%
Other values (119) 16632
63.0%
ValueCountFrequency (%)
0 34
 
0.1%
1 827
3.1%
2 951
3.6%
3 983
3.7%
4 1008
3.8%
5 956
3.6%
6 994
3.8%
7 928
3.5%
8 993
3.8%
9 892
3.4%
ValueCountFrequency (%)
208 1
< 0.1%
136 1
< 0.1%
135 1
< 0.1%
130 1
< 0.1%
129 1
< 0.1%
128 1
< 0.1%
127 1
< 0.1%
126 1
< 0.1%
125 1
< 0.1%
124 1
< 0.1%

grid
Real number (ℝ)

ZEROS 

Distinct35
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.151255
Minimum0
Maximum34
Zeros1627
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-25T01:11:34.110860image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median11
Q317
95-th percentile23
Maximum34
Range34
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.217744
Coefficient of variation (CV)0.64725846
Kurtosis-0.92710449
Mean11.151255
Median Absolute Deviation (MAD)6
Skewness0.19316088
Sum294605
Variance52.095828
MonotonicityNot monotonic
2024-06-25T01:11:34.380077image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0 1627
 
6.2%
1 1119
 
4.2%
7 1118
 
4.2%
4 1115
 
4.2%
11 1115
 
4.2%
9 1115
 
4.2%
5 1115
 
4.2%
3 1113
 
4.2%
10 1113
 
4.2%
8 1112
 
4.2%
Other values (25) 14757
55.9%
ValueCountFrequency (%)
0 1627
6.2%
1 1119
4.2%
2 1108
4.2%
3 1113
4.2%
4 1115
4.2%
5 1115
4.2%
6 1108
4.2%
7 1118
4.2%
8 1112
4.2%
9 1115
4.2%
ValueCountFrequency (%)
34 1
 
< 0.1%
33 13
 
< 0.1%
32 17
 
0.1%
31 18
 
0.1%
30 19
 
0.1%
29 25
 
0.1%
28 30
 
0.1%
27 46
 
0.2%
26 248
0.9%
25 301
1.1%

position
Real number (ℝ)

HIGH CORRELATION 

Distinct33
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.928612
Minimum1
Maximum33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-25T01:11:34.685826image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q39
95-th percentile15
Maximum33
Range32
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.4397335
Coefficient of variation (CV)0.74886558
Kurtosis0.75630368
Mean5.928612
Median Absolute Deviation (MAD)1
Skewness1.2612153
Sum156628
Variance19.711233
MonotonicityNot monotonic
2024-06-25T01:11:34.960456image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
3 12035
45.6%
4 1118
 
4.2%
2 1116
 
4.2%
5 1114
 
4.2%
1 1111
 
4.2%
6 1107
 
4.2%
7 1087
 
4.1%
8 1059
 
4.0%
9 1021
 
3.9%
10 961
 
3.6%
Other values (23) 4690
 
17.8%
ValueCountFrequency (%)
1 1111
 
4.2%
2 1116
 
4.2%
3 12035
45.6%
4 1118
 
4.2%
5 1114
 
4.2%
6 1107
 
4.2%
7 1087
 
4.1%
8 1059
 
4.0%
9 1021
 
3.9%
10 961
 
3.6%
ValueCountFrequency (%)
33 1
 
< 0.1%
32 1
 
< 0.1%
31 1
 
< 0.1%
30 1
 
< 0.1%
29 1
 
< 0.1%
28 1
 
< 0.1%
27 1
 
< 0.1%
26 1
 
< 0.1%
25 1
 
< 0.1%
24 3
< 0.1%

positionText
Categorical

HIGH CORRELATION 

Distinct37
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.5 MiB
F
10383 
3
 
1118
4
 
1118
2
 
1116
5
 
1114
Other values (32)
11570 

Length

Max length2
Median length1
Mean length1.2139748
Min length1

Characters and Unicode

Total characters32072
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row2
3rd row3
4th row4
5th row5

Common Values

ValueCountFrequency (%)
F 10383
39.3%
3 1118
 
4.2%
4 1118
 
4.2%
2 1116
 
4.2%
5 1114
 
4.2%
1 1111
 
4.2%
6 1107
 
4.2%
7 1087
 
4.1%
8 1059
 
4.0%
9 1021
 
3.9%
Other values (27) 6185
23.4%

Length

2024-06-25T01:11:35.234941image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
f 10383
39.3%
3 1118
 
4.2%
4 1118
 
4.2%
2 1116
 
4.2%
5 1114
 
4.2%
1 1111
 
4.2%
6 1107
 
4.2%
7 1087
 
4.1%
8 1059
 
4.0%
9 1021
 
3.9%
Other values (27) 6185
23.4%

Most occurring characters

ValueCountFrequency (%)
F 10383
32.4%
1 7542
23.5%
2 2057
 
6.4%
3 1827
 
5.7%
4 1710
 
5.3%
5 1626
 
5.1%
6 1526
 
4.8%
7 1411
 
4.4%
8 1272
 
4.0%
9 1155
 
3.6%
Other values (4) 1563
 
4.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 32072
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
F 10383
32.4%
1 7542
23.5%
2 2057
 
6.4%
3 1827
 
5.7%
4 1710
 
5.3%
5 1626
 
5.1%
6 1526
 
4.8%
7 1411
 
4.4%
8 1272
 
4.0%
9 1155
 
3.6%
Other values (4) 1563
 
4.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 32072
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
F 10383
32.4%
1 7542
23.5%
2 2057
 
6.4%
3 1827
 
5.7%
4 1710
 
5.3%
5 1626
 
5.1%
6 1526
 
4.8%
7 1411
 
4.4%
8 1272
 
4.0%
9 1155
 
3.6%
Other values (4) 1563
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 32072
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
F 10383
32.4%
1 7542
23.5%
2 2057
 
6.4%
3 1827
 
5.7%
4 1710
 
5.3%
5 1626
 
5.1%
6 1526
 
4.8%
7 1411
 
4.4%
8 1272
 
4.0%
9 1155
 
3.6%
Other values (4) 1563
 
4.9%

positionOrder
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.823574
Minimum1
Maximum39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-25T01:11:35.503648image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median12
Q318
95-th percentile26
Maximum39
Range38
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.682877
Coefficient of variation (CV)0.59912135
Kurtosis-0.4818229
Mean12.823574
Median Absolute Deviation (MAD)6
Skewness0.3971628
Sum338786
Variance59.026598
MonotonicityNot monotonic
2024-06-25T01:11:35.794839image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
3 1118
 
4.2%
4 1118
 
4.2%
2 1117
 
4.2%
11 1116
 
4.2%
5 1115
 
4.2%
6 1115
 
4.2%
7 1115
 
4.2%
8 1115
 
4.2%
9 1114
 
4.2%
10 1113
 
4.2%
Other values (29) 15263
57.8%
ValueCountFrequency (%)
1 1111
4.2%
2 1117
4.2%
3 1118
4.2%
4 1118
4.2%
5 1115
4.2%
6 1115
4.2%
7 1115
4.2%
8 1115
4.2%
9 1114
4.2%
10 1113
4.2%
ValueCountFrequency (%)
39 13
 
< 0.1%
38 17
 
0.1%
37 17
 
0.1%
36 18
 
0.1%
35 29
 
0.1%
34 46
 
0.2%
33 65
0.2%
32 79
0.3%
31 117
0.4%
30 156
0.6%

points
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct39
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9477289
Minimum0
Maximum50
Zeros18419
Zeros (%)69.7%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-25T01:11:36.086390image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile10
Maximum50
Range50
Interquartile range (IQR)2

Descriptive statistics

Standard deviation4.2874056
Coefficient of variation (CV)2.2012332
Kurtosis11.109091
Mean1.9477289
Median Absolute Deviation (MAD)0
Skewness3.0827107
Sum51457.05
Variance18.381847
MonotonicityNot monotonic
2024-06-25T01:11:36.365437image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
0 18419
69.7%
2 1109
 
4.2%
4 1095
 
4.1%
6 1075
 
4.1%
1 1050
 
4.0%
3 823
 
3.1%
10 597
 
2.3%
8 458
 
1.7%
9 443
 
1.7%
12 278
 
1.1%
Other values (29) 1072
 
4.1%
ValueCountFrequency (%)
0 18419
69.7%
0.5 6
 
< 0.1%
1 1050
 
4.0%
1.33 3
 
< 0.1%
1.5 17
 
0.1%
2 1109
 
4.2%
2.5 1
 
< 0.1%
3 823
 
3.1%
3.14 1
 
< 0.1%
3.5 1
 
< 0.1%
ValueCountFrequency (%)
50 1
 
< 0.1%
36 1
 
< 0.1%
30 1
 
< 0.1%
26 35
 
0.1%
25 251
1.0%
24 1
 
< 0.1%
20 1
 
< 0.1%
19 22
 
0.1%
18 264
1.0%
16 11
 
< 0.1%

laps
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct172
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.169499
Minimum0
Maximum200
Zeros2519
Zeros (%)9.5%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-25T01:11:36.649580image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q123
median53
Q366
95-th percentile79
Maximum200
Range200
Interquartile range (IQR)43

Descriptive statistics

Standard deviation29.598762
Coefficient of variation (CV)0.64108909
Kurtosis3.6900793
Mean46.169499
Median Absolute Deviation (MAD)17
Skewness0.71087761
Sum1219752
Variance876.08672
MonotonicityNot monotonic
2024-06-25T01:11:36.964948image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2519
 
9.5%
70 958
 
3.6%
53 924
 
3.5%
52 801
 
3.0%
56 796
 
3.0%
57 694
 
2.6%
69 663
 
2.5%
71 628
 
2.4%
55 581
 
2.2%
58 557
 
2.1%
Other values (162) 17298
65.5%
ValueCountFrequency (%)
0 2519
9.5%
1 307
 
1.2%
2 228
 
0.9%
3 199
 
0.8%
4 183
 
0.7%
5 196
 
0.7%
6 183
 
0.7%
7 166
 
0.6%
8 187
 
0.7%
9 178
 
0.7%
ValueCountFrequency (%)
200 123
0.5%
199 4
 
< 0.1%
197 5
 
< 0.1%
196 15
 
0.1%
195 4
 
< 0.1%
194 4
 
< 0.1%
193 7
 
< 0.1%
192 1
 
< 0.1%
191 8
 
< 0.1%
190 2
 
< 0.1%

milliseconds
Real number (ℝ)

HIGH CORRELATION 

Distinct7436
Distinct (%)28.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11981667
Minimum207071
Maximum15090540
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-25T01:11:37.281263image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum207071
5-th percentile5263005
Q17392292
median14259460
Q314259460
95-th percentile14259460
Maximum15090540
Range14883469
Interquartile range (IQR)6867168

Descriptive statistics

Standard deviation3731085.1
Coefficient of variation (CV)0.3113995
Kurtosis-0.73318149
Mean11981667
Median Absolute Deviation (MAD)0
Skewness-1.0797599
Sum3.1654365 × 1011
Variance1.3920996 × 1013
MonotonicityNot monotonic
2024-06-25T01:11:37.596050image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14259460 18947
71.7%
10928200 3
 
< 0.1%
12131000 2
 
< 0.1%
14233190 2
 
< 0.1%
13642300 2
 
< 0.1%
5152531 2
 
< 0.1%
5808819 2
 
< 0.1%
14429440 2
 
< 0.1%
5262136 2
 
< 0.1%
5350182 2
 
< 0.1%
Other values (7426) 7453
 
28.2%
ValueCountFrequency (%)
207071 1
< 0.1%
209066 1
< 0.1%
209672 1
< 0.1%
211567 1
< 0.1%
214550 1
< 0.1%
217248 1
< 0.1%
218650 1
< 0.1%
219679 1
< 0.1%
222556 1
< 0.1%
223237 1
< 0.1%
ValueCountFrequency (%)
15090540 1
< 0.1%
14977530 1
< 0.1%
14926980 1
< 0.1%
14823600 1
< 0.1%
14779660 1
< 0.1%
14743144 1
< 0.1%
14729991 1
< 0.1%
14726593 1
< 0.1%
14724654 1
< 0.1%
14715501 1
< 0.1%

fastestLap
Real number (ℝ)

Distinct80
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.753473
Minimum1
Maximum85
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-25T01:11:37.916991image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile24
Q150
median50
Q350
95-th percentile57
Maximum85
Range84
Interquartile range (IQR)0

Descriptive statistics

Standard deviation9.7624084
Coefficient of variation (CV)0.20443347
Kurtosis7.152841
Mean47.753473
Median Absolute Deviation (MAD)0
Skewness-2.2503549
Sum1261599
Variance95.304617
MonotonicityNot monotonic
2024-06-25T01:11:38.209366image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50 18776
71.1%
52 273
 
1.0%
53 272
 
1.0%
51 257
 
1.0%
48 219
 
0.8%
49 214
 
0.8%
55 212
 
0.8%
44 209
 
0.8%
43 204
 
0.8%
54 204
 
0.8%
Other values (70) 5579
 
21.1%
ValueCountFrequency (%)
1 10
 
< 0.1%
2 55
0.2%
3 32
0.1%
4 55
0.2%
5 41
0.2%
6 54
0.2%
7 41
0.2%
8 42
0.2%
9 49
0.2%
10 51
0.2%
ValueCountFrequency (%)
85 2
 
< 0.1%
80 3
 
< 0.1%
78 6
 
< 0.1%
77 12
< 0.1%
76 13
< 0.1%
75 16
0.1%
74 21
0.1%
73 5
 
< 0.1%
72 15
0.1%
71 27
0.1%

rank
Real number (ℝ)

Distinct25
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.8991256
Minimum0
Maximum24
Zeros229
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-25T01:11:38.621629image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q34
95-th percentile17
Maximum24
Range24
Interquartile range (IQR)3

Descriptive statistics

Standard deviation5.5163271
Coefficient of variation (CV)1.41476
Kurtosis1.8570525
Mean3.8991256
Median Absolute Deviation (MAD)0
Skewness1.7795532
Sum103011
Variance30.429865
MonotonicityNot monotonic
2024-06-25T01:11:39.102451image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1 18643
70.6%
2 394
 
1.5%
3 394
 
1.5%
4 394
 
1.5%
6 394
 
1.5%
5 394
 
1.5%
7 393
 
1.5%
9 393
 
1.5%
11 393
 
1.5%
10 393
 
1.5%
Other values (15) 4234
 
16.0%
ValueCountFrequency (%)
0 229
 
0.9%
1 18643
70.6%
2 394
 
1.5%
3 394
 
1.5%
4 394
 
1.5%
5 394
 
1.5%
6 394
 
1.5%
7 393
 
1.5%
8 393
 
1.5%
9 393
 
1.5%
ValueCountFrequency (%)
24 28
 
0.1%
23 43
 
0.2%
22 91
 
0.3%
21 122
 
0.5%
20 278
1.1%
19 335
1.3%
18 374
1.4%
17 384
1.5%
16 390
1.5%
15 391
1.5%

fastestLapSpeed
Real number (ℝ)

Distinct7443
Distinct (%)28.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean206.0805
Minimum89.54
Maximum257.32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-25T01:11:39.542014image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum89.54
5-th percentile188.0247
Q1207.069
median207.069
Q3207.069
95-th percentile223.2656
Maximum257.32
Range167.78
Interquartile range (IQR)0

Descriptive statistics

Standard deviation11.81515
Coefficient of variation (CV)0.057332692
Kurtosis10.900828
Mean206.0805
Median Absolute Deviation (MAD)0
Skewness-1.6388823
Sum5444440.8
Variance139.59777
MonotonicityNot monotonic
2024-06-25T01:11:41.735857image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
207.069 18482
70.0%
202.871 3
 
< 0.1%
204.946 3
 
< 0.1%
209.244 3
 
< 0.1%
217.668 3
 
< 0.1%
201.33 3
 
< 0.1%
201.527 3
 
< 0.1%
202.685 3
 
< 0.1%
201.478 3
 
< 0.1%
225.876 3
 
< 0.1%
Other values (7433) 7910
29.9%
ValueCountFrequency (%)
89.54 1
< 0.1%
91.61 1
< 0.1%
100.615 1
< 0.1%
101.399 1
< 0.1%
101.884 1
< 0.1%
108.41 1
< 0.1%
112.116 1
< 0.1%
117.753 1
< 0.1%
118.872 1
< 0.1%
121.027 1
< 0.1%
ValueCountFrequency (%)
257.32 1
< 0.1%
256.324 1
< 0.1%
255.874 1
< 0.1%
255.014 1
< 0.1%
254.861 1
< 0.1%
253.874 1
< 0.1%
253.566 1
< 0.1%
252.794 1
< 0.1%
252.77 1
< 0.1%
252.604 1
< 0.1%

statusId
Real number (ℝ)

HIGH CORRELATION 

Distinct137
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.363261
Minimum1
Maximum141
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-25T01:11:42.299265image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median10
Q314
95-th percentile81
Maximum141
Range140
Interquartile range (IQR)13

Descriptive statistics

Standard deviation26.11787
Coefficient of variation (CV)1.504203
Kurtosis4.0978449
Mean17.363261
Median Absolute Deviation (MAD)9
Skewness2.2200757
Sum458720
Variance682.14311
MonotonicityNot monotonic
2024-06-25T01:11:42.840293image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 7472
28.3%
11 3954
15.0%
5 2022
 
7.7%
12 1600
 
6.1%
3 1057
 
4.0%
81 1025
 
3.9%
4 843
 
3.2%
6 809
 
3.1%
20 792
 
3.0%
13 731
 
2.8%
Other values (127) 6114
23.1%
ValueCountFrequency (%)
1 7472
28.3%
2 145
 
0.5%
3 1057
 
4.0%
4 843
 
3.2%
5 2022
 
7.7%
6 809
 
3.1%
7 321
 
1.2%
8 214
 
0.8%
9 138
 
0.5%
10 316
 
1.2%
ValueCountFrequency (%)
141 1
 
< 0.1%
140 4
 
< 0.1%
139 3
 
< 0.1%
138 1
 
< 0.1%
137 2
 
< 0.1%
136 1
 
< 0.1%
135 1
 
< 0.1%
132 5
 
< 0.1%
131 41
0.2%
130 58
0.2%

Interactions

2024-06-25T01:11:24.743769image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:17.533757image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:21.416749image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:26.430067image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:31.905155image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:35.750082image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:40.981451image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:45.462463image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:49.403340image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:54.256385image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:00.942087image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:05.709229image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:10.912596image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:15.934754image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:20.359698image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:25.140150image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:17.785329image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:21.669782image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:28.284359image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:32.147857image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:35.983348image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:41.354485image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:45.744367image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:49.681401image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:54.648045image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:01.281427image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:05.975787image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:11.570448image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:16.191571image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:20.614173image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:25.526993image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:18.019216image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:21.934509image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:28.553989image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:32.395258image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:36.221154image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:41.740094image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:46.014842image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:49.937542image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:55.017373image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:01.541761image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:06.241627image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:12.115987image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:16.443553image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:20.886039image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:25.913381image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:18.266617image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:22.155738image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:28.799239image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:32.652840image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:36.462981image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:42.102645image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:46.263993image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:50.177598image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:55.596210image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:01.937170image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:06.484339image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:12.467720image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:16.718518image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:21.137591image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:26.263659image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:18.514922image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:22.399092image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:29.047204image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:32.896405image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:36.715970image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:42.466874image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:46.512135image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:50.440307image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:56.139365image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:02.247746image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:06.739913image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:12.821877image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:16.974315image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:21.382738image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:26.641775image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:18.796264image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:22.669294image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:29.307035image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:33.137262image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:36.946406image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:42.731416image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:46.756288image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:50.727904image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:56.768297image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:02.698604image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:06.990482image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:13.223732image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:17.217425image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:21.652620image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:27.042866image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:19.055728image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:23.059779image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:29.577720image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:33.405248image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:37.196362image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:43.017800image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:47.011723image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:50.990896image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:57.466700image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:03.160170image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:07.266390image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:13.591022image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:17.469808image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:21.927302image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:27.462362image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:19.309392image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:23.406890image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:29.821747image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:33.683244image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:37.466641image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:43.308621image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:47.273111image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:51.250279image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:58.664946image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:03.429328image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:07.546708image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:13.848216image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:17.760695image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:22.171777image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:27.923826image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:19.586591image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:23.783462image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:30.090292image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:33.970288image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:37.772758image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:43.595476image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:47.535981image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:51.549460image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:58.933981image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:03.742685image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:07.839085image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:14.108076image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:18.023618image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:22.456655image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:28.313752image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:19.851275image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:24.162220image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:30.352404image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:34.200364image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:38.097559image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:43.856749image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:47.788366image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:51.818845image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:59.183100image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:04.024998image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:08.109586image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:14.349377image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:18.263492image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:22.716178image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:28.592921image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:20.126424image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:24.575533image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:30.633774image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:34.456135image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:38.474389image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:44.137632image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:48.063444image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:52.090632image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:59.464440image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:04.303476image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:08.535126image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:14.640003image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:18.534635image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:23.003491image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:28.877724image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:20.394238image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:24.922127image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:30.898164image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:34.738654image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:38.890103image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:44.418945image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:48.350455image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:52.388508image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:59.759464image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:04.611038image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:08.945649image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:14.903969image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:18.821767image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:23.267629image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:29.133382image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:20.644871image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:25.259908image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:31.130149image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:34.982653image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:39.267259image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:44.664171image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:48.622438image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:53.040879image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:00.094983image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:04.879065image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:09.336274image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:15.140494image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:19.074791image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:23.535684image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:29.411352image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:20.901139image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:25.631412image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:31.386550image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:35.226248image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:39.660748image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:44.912776image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:48.872355image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:53.478667image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:00.347055image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:05.148094image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:09.661103image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:15.380922image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:19.847659image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:23.972910image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:29.676885image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:21.151313image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:26.033569image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:31.639965image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:35.482850image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:40.081919image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:45.197047image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:49.129987image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:10:53.867162image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:00.636956image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:05.417620image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:10.201318image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:15.670247image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:20.101588image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-25T01:11:24.342663image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2024-06-25T01:11:43.206934image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
constructorIddriverIdfastestLapfastestLapSpeedgridlapsmillisecondsnumberpointspositionpositionOrderpositionTextraceIdrankresultIdstatusId
constructorId1.0000.3190.0660.0080.173-0.1080.2520.285-0.2190.0280.2030.1540.325-0.1550.3020.261
driverId0.3191.0000.0580.0090.069-0.0020.1100.253-0.0790.0890.0680.1430.7030.0040.6640.104
fastestLap0.0660.0581.000-0.010-0.0130.1280.0140.0140.0290.021-0.0500.1280.032-0.2830.0220.011
fastestLapSpeed0.0080.009-0.0101.000-0.060-0.078-0.113-0.0090.038-0.058-0.0520.116-0.057-0.161-0.083-0.034
grid0.1730.069-0.013-0.0601.0000.0460.3270.210-0.4000.3760.2180.235-0.0300.070-0.0250.171
laps-0.108-0.0020.128-0.0780.0461.000-0.310-0.1240.4200.374-0.6830.2760.0780.1840.086-0.291
milliseconds0.2520.1100.014-0.1130.327-0.3101.0000.209-0.7500.1000.6440.247-0.083-0.236-0.1130.766
number0.2850.2530.014-0.0090.210-0.1240.2091.000-0.2190.1110.2480.0980.1830.0080.1700.232
points-0.219-0.0790.0290.038-0.4000.420-0.750-0.2191.000-0.239-0.7830.4200.1360.1480.153-0.621
position0.0280.0890.021-0.0580.3760.3740.1000.111-0.2391.000-0.0440.9990.1160.3640.1400.099
positionOrder0.2030.068-0.050-0.0520.218-0.6830.6440.248-0.783-0.0441.0000.606-0.060-0.073-0.0660.567
positionText0.1540.1430.1280.1160.2350.2760.2470.0980.4200.9990.6061.000-0.116-0.300-0.1390.362
raceId0.3250.7030.032-0.057-0.0300.078-0.0830.1830.1360.116-0.060-0.1161.0000.2690.968-0.065
rank-0.1550.004-0.283-0.1610.0700.184-0.2360.0080.1480.364-0.073-0.3000.2691.0000.344-0.207
resultId0.3020.6640.022-0.083-0.0250.086-0.1130.1700.1530.140-0.066-0.1390.9680.3441.000-0.093
statusId0.2610.1040.011-0.0340.171-0.2910.7660.232-0.6210.0990.5670.362-0.065-0.207-0.0931.000

Missing values

2024-06-25T01:11:30.067955image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2024-06-25T01:11:30.650506image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

resultIdraceIddriverIdconstructorIdnumbergridpositionpositionTextpositionOrderpointslapsmillisecondsfastestLaprankfastestLapSpeedstatusId
01181122111110.0585690616392218.3001
121822352228.0585696094413217.5861
231833773336.0585698779415216.7191
3418445114445.0585707797587215.4641
4518512335554.0585708630431218.3851
5618638136663.057142594605014212.97411
67187514177772.05514259460548213.2245
7818861158881.05314259460204217.1805
891892423F90.04714259460159215.1004
9101810712183F100.043142594602313213.1663
resultIdraceIddriverIdconstructorIdnumbergridpositionpositionTextpositionOrderpointslapsmillisecondsfastestLaprankfastestLapSpeedstatusId
2640926415112780721027101111110.06214259460320216.30811
2641026416112782521020181212120.062142594605812218.15311
26411264171127817215391313130.062142594601319216.65511
2641226418112783921431121414140.062142594603716217.36111
264132641911278551524171515150.062142594603713218.13411
2641426420112784221410151616160.062142594601017217.18311
2641526421112785832191717170.062142594605514217.56211
264162642211278221577161818180.062142594601118216.95911
26417264231127411714201919190.06214259460622223.68911
26418264241127848323143F200.051142594604815217.44231